There is an abundance of information available on the Internet through content on web pages, social networks, user generated content, and other sources of information, which are all accessible via the world-wide web (WWW). Search systems make the access to such information speedy and generally cost effective. However, there are also certain disadvantages, one of which is the fact that even targeted searches for generally available information result in large amounts of ‘hits’ requiring the user to sift through a lot of unwanted information. The search is static by nature and over time, as more and more irrelevant data becomes available, the more difficult it is to get to meaningful information.
Various users of information are interested in a more elaborate analysis of the information available through the Internet as well as the time-value of such information. That is, older information may be less important than newer information and the trends relating to the information may be more interesting than the data relating to the information at any given point in time. Current solutions monitor online behavior, rather than attempting to reach intents. For example, today advertisers attempting to target customers can only do so based on where the customers go, what they do, and what they read on the web.
Today, advertising is all about demographics and does not handle true intent. However, advertisers are trying to target persons based on, for example, their age and music preferences. An effective way for detecting demographic information related to users in a broad sense would therefore be advantageous.